区域总量控制下的冬小麦种植面积空间分布优化

【目的】利用传统遥感与抽样相结合的方法进行农作物种植面积测量,只能获得区域总量,无法有效获取农作物种植面积空间分布信息。针对以上不足,开展区域总量控制下的冬小麦种植面积空间分布优化研究,从而提高冬小麦种植面积测量的空间分布精度。【方法】将整个遥感影像像元划分为3部分:"纯净冬小麦像元"、"混合冬小麦像元"和"典型非冬小麦像元"。综合软、硬分类方法各自的优势,在区域冬小麦总量面积一定的前提下,设定阈值确定混合冬小麦像元的空间分布范围。【结果】传统遥感与抽样相结合的方法提取出的冬小麦结果RMSE为0.13,优于硬分类方法(RMSE为0.16)和软分类方法(RMSE为0.20)。【结论】区域总量控制下的软、硬分类方法能够有效地对冬小麦种植面积空间分布进行优化,既保证了区域测量精度,又提高了空间分布的准确性。

Spatial Distribution Optimization of Wheat Planting Area Based on Regional Area Control

【Objective】 According to disadvantage of traditional method combing remote sensing and sampling method which only obtains the regional area, this paper brought up a new method for optimizing wheat distribution with the whole regional area.【Method】 Incorporating the advantages of soft and hard classification, the wheat extent can be divided into three parts, pure, mixed and non-wheat pixels. Based on the regional winter area, the threshold was set and the winter area was obtained, which improved not only the regional accuracy but also spatial distribution accuracy. 【Result】 The result shows that RMSE of proposed method is 0.13, which is better than hard classification result and soft classification result, which is 0.16 and 0.20, respectively. All above verifies the proposed method is effective. 【Conclusion】 Winter wheat area method with regional area control provides a good basis for the large scale crop planting area survey.